org.bytedeco.javacpp

Class opencv_optflow

java.lang.Object

org.bytedeco.javacpp.presets.opencv_optflow

org.bytedeco.javacpp.opencv_optflow

All Implemented Interfaces:

InfoMapper

public class opencv_optflow
extends opencv_optflow

Constructor Summary

Constructors

Constructor and Description
opencv_optflow()

Method Summary

Methods

Modifier and Type	Method and Description
static double	calcGlobalOrientation(opencv_core.Mat orientation, opencv_core.Mat mask, opencv_core.Mat mhi, double timestamp, double duration) \brief Calculates a global motion orientation in a selected region.
static void	calcMotionGradient(opencv_core.Mat mhi, opencv_core.Mat mask, opencv_core.Mat orientation, double delta1, double delta2)
static void	calcMotionGradient(opencv_core.Mat mhi, opencv_core.Mat mask, opencv_core.Mat orientation, double delta1, double delta2, int apertureSize) \brief Calculates a gradient orientation of a motion history image.
static void	calcOpticalFlowSF(opencv_core.Mat from, opencv_core.Mat to, opencv_core.Mat flow, int layers, int averaging_block_size, int max_flow) \addtogroup optflow \{
static void	calcOpticalFlowSF(opencv_core.Mat from, opencv_core.Mat to, opencv_core.Mat flow, int layers, int averaging_block_size, int max_flow, double sigma_dist, double sigma_color, int postprocess_window, double sigma_dist_fix, double sigma_color_fix, double occ_thr, int upscale_averaging_radius, double upscale_sigma_dist, double upscale_sigma_color, double speed_up_thr) \brief Calculate an optical flow using "SimpleFlow" algorithm.
static void	calcOpticalFlowSparseToDense(opencv_core.Mat from, opencv_core.Mat to, opencv_core.Mat flow)
static void	calcOpticalFlowSparseToDense(opencv_core.Mat from, opencv_core.Mat to, opencv_core.Mat flow, int grid_step, int k, float sigma, boolean use_post_proc, float fgs_lambda, float fgs_sigma) \brief Fast dense optical flow based on PyrLK sparse matches interpolation.
static opencv_video.DenseOpticalFlow	createOptFlow_DeepFlow() \brief DeepFlow optical flow algorithm implementation.
static opencv_video.DenseOpticalFlow	createOptFlow_Farneback() Additional interface to the Farneback's algorithm - calcOpticalFlowFarneback()
static opencv_video.DenseOpticalFlow	createOptFlow_SimpleFlow() Additional interface to the SimpleFlow algorithm - calcOpticalFlowSF()
static opencv_video.DenseOpticalFlow	createOptFlow_SparseToDense() Additional interface to the SparseToDenseFlow algorithm - calcOpticalFlowSparseToDense()
static opencv_core.Mat	readOpticalFlow(BytePointer path) \brief Read a .flo file
static opencv_core.Mat	readOpticalFlow(String path)
static void	segmentMotion(opencv_core.Mat mhi, opencv_core.Mat segmask, opencv_core.RectVector boundingRects, double timestamp, double segThresh) \brief Splits a motion history image into a few parts corresponding to separate independent motions (for example, left hand, right hand).
static void	updateMotionHistory(opencv_core.Mat silhouette, opencv_core.Mat mhi, double timestamp, double duration) \addtogroup optflow \{
static boolean	writeOpticalFlow(BytePointer path, opencv_core.Mat flow) \brief Write a .flo to disk
static boolean	writeOpticalFlow(String path, opencv_core.Mat flow)

Methods inherited from class org.bytedeco.javacpp.presets.opencv_optflow

map

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

opencv_optflow

public opencv_optflow()

Method Detail

calcOpticalFlowSF

@Namespace(value="cv::optflow")
public static void calcOpticalFlowSF(@ByVal
                                    opencv_core.Mat from,
                                    @ByVal
                                    opencv_core.Mat to,
                                    @ByVal
                                    opencv_core.Mat flow,
                                    int layers,
                                    int averaging_block_size,
                                    int max_flow)

\addtogroup optflow \{

/** \overload

calcOpticalFlowSF

@Namespace(value="cv::optflow")
public static void calcOpticalFlowSF(@ByVal
                                    opencv_core.Mat from,
                                    @ByVal
                                    opencv_core.Mat to,
                                    @ByVal
                                    opencv_core.Mat flow,
                                    int layers,
                                    int averaging_block_size,
                                    int max_flow,
                                    double sigma_dist,
                                    double sigma_color,
                                    int postprocess_window,
                                    double sigma_dist_fix,
                                    double sigma_color_fix,
                                    double occ_thr,
                                    int upscale_averaging_radius,
                                    double upscale_sigma_dist,
                                    double upscale_sigma_color,
                                    double speed_up_thr)

\brief Calculate an optical flow using "SimpleFlow" algorithm.

Parameters:

from - First 8-bit 3-channel image.

to - Second 8-bit 3-channel image of the same size as prev

flow - computed flow image that has the same size as prev and type CV_32FC2

layers - Number of layers

averaging_block_size - Size of block through which we sum up when calculate cost function for pixel

max_flow - maximal flow that we search at each level

sigma_dist - vector smooth spatial sigma parameter

sigma_color - vector smooth color sigma parameter

postprocess_window - window size for postprocess cross bilateral filter

sigma_dist_fix - spatial sigma for postprocess cross bilateralf filter

sigma_color_fix - color sigma for postprocess cross bilateral filter

occ_thr - threshold for detecting occlusions

upscale_averaging_radius - window size for bilateral upscale operation

upscale_sigma_dist - spatial sigma for bilateral upscale operation

upscale_sigma_color - color sigma for bilateral upscale operation

speed_up_thr - threshold to detect point with irregular flow - where flow should be recalculated after upscale

See \cite Tao2012 . And site of project - .

\note - An example using the simpleFlow algorithm can be found at samples/simpleflow_demo.cpp

calcOpticalFlowSparseToDense

@Namespace(value="cv::optflow")
public static void calcOpticalFlowSparseToDense(@ByVal
                                               opencv_core.Mat from,
                                               @ByVal
                                               opencv_core.Mat to,
                                               @ByVal
                                               opencv_core.Mat flow,
                                               int grid_step,
                                               int k,
                                               float sigma,
                                               @Cast(value="bool")
                                               boolean use_post_proc,
                                               float fgs_lambda,
                                               float fgs_sigma)

\brief Fast dense optical flow based on PyrLK sparse matches interpolation.

Parameters:

from - first 8-bit 3-channel or 1-channel image.

to - second 8-bit 3-channel or 1-channel image of the same size as from

flow - computed flow image that has the same size as from and CV_32FC2 type

grid_step - stride used in sparse match computation. Lower values usually result in higher quality but slow down the algorithm.

k - number of nearest-neighbor matches considered, when fitting a locally affine model. Lower values can make the algorithm noticeably faster at the cost of some quality degradation.

sigma - parameter defining how fast the weights decrease in the locally-weighted affine fitting. Higher values can help preserve fine details, lower values can help to get rid of the noise in the output flow.

use_post_proc - defines whether the ximgproc::fastGlobalSmootherFilter() is used for post-processing after interpolation

fgs_lambda - see the respective parameter of the ximgproc::fastGlobalSmootherFilter()

fgs_sigma - see the respective parameter of the ximgproc::fastGlobalSmootherFilter()

calcOpticalFlowSparseToDense

@Namespace(value="cv::optflow")
public static void calcOpticalFlowSparseToDense(@ByVal
                                               opencv_core.Mat from,
                                               @ByVal
                                               opencv_core.Mat to,
                                               @ByVal
                                               opencv_core.Mat flow)

readOpticalFlow

@Namespace(value="cv::optflow")
@ByVal
public static opencv_core.Mat readOpticalFlow(@opencv_core.Str
                                                   BytePointer path)

\brief Read a .flo file

Parameters:

path - Path to the file to be loaded

The function readOpticalFlow loads a flow field from a file and returns it as a single matrix. Resulting Mat has a type CV_32FC2 - floating-point, 2-channel. First channel corresponds to the flow in the horizontal direction (u), second - vertical (v).

readOpticalFlow

@Namespace(value="cv::optflow")
@ByVal
public static opencv_core.Mat readOpticalFlow(@opencv_core.Str
                                                   String path)

writeOpticalFlow

@Namespace(value="cv::optflow")
@Cast(value="bool")
public static boolean writeOpticalFlow(@opencv_core.Str
                                                BytePointer path,
                                                @ByVal
                                                opencv_core.Mat flow)

\brief Write a .flo to disk

Parameters:

path - Path to the file to be written

flow - Flow field to be stored

The function stores a flow field in a file, returns true on success, false otherwise. The flow field must be a 2-channel, floating-point matrix (CV_32FC2). First channel corresponds to the flow in the horizontal direction (u), second - vertical (v).

writeOpticalFlow

@Namespace(value="cv::optflow")
@Cast(value="bool")
public static boolean writeOpticalFlow(@opencv_core.Str
                                                String path,
                                                @ByVal
                                                opencv_core.Mat flow)

createOptFlow_DeepFlow

@Namespace(value="cv::optflow")
@opencv_core.Ptr
public static opencv_video.DenseOpticalFlow createOptFlow_DeepFlow()

\brief DeepFlow optical flow algorithm implementation.

The class implements the DeepFlow optical flow algorithm described in \cite Weinzaepfel2013 . See also . Parameters - class fields - that may be modified after creating a class instance: - member float alpha Smoothness assumption weight - member float delta Color constancy assumption weight - member float gamma Gradient constancy weight - member float sigma Gaussian smoothing parameter - member int minSize Minimal dimension of an image in the pyramid (next, smaller images in the pyramid are generated until one of the dimensions reaches this size) - member float downscaleFactor Scaling factor in the image pyramid (must be \< 1) - member int fixedPointIterations How many iterations on each level of the pyramid - member int sorIterations Iterations of Succesive Over-Relaxation (solver) - member float omega Relaxation factor in SOR

createOptFlow_SimpleFlow

@Namespace(value="cv::optflow")
@opencv_core.Ptr
public static opencv_video.DenseOpticalFlow createOptFlow_SimpleFlow()

Additional interface to the SimpleFlow algorithm - calcOpticalFlowSF()

createOptFlow_Farneback

@Namespace(value="cv::optflow")
@opencv_core.Ptr
public static opencv_video.DenseOpticalFlow createOptFlow_Farneback()

Additional interface to the Farneback's algorithm - calcOpticalFlowFarneback()

createOptFlow_SparseToDense

@Namespace(value="cv::optflow")
@opencv_core.Ptr
public static opencv_video.DenseOpticalFlow createOptFlow_SparseToDense()

Additional interface to the SparseToDenseFlow algorithm - calcOpticalFlowSparseToDense()

updateMotionHistory

@Namespace(value="cv::motempl")
public static void updateMotionHistory(@ByVal
                                      opencv_core.Mat silhouette,
                                      @ByVal
                                      opencv_core.Mat mhi,
                                      double timestamp,
                                      double duration)

\addtogroup optflow \{

/** \brief Updates the motion history image by a moving silhouette.

Parameters:

silhouette - Silhouette mask that has non-zero pixels where the motion occurs.

mhi - Motion history image that is updated by the function (single-channel, 32-bit floating-point).

timestamp - Current time in milliseconds or other units.

duration - Maximal duration of the motion track in the same units as timestamp .

The function updates the motion history image as follows:

\f[\texttt{mhi} (x,y)= \forkthree{\texttt{timestamp}}{if \(\texttt{silhouette}(x,y) \ne 0\)}{0}{if \(\texttt{silhouette}(x,y) = 0\) and \(\texttt{mhi} < (\texttt{timestamp} - \texttt{duration})\)}{\texttt{mhi}(x,y)}{otherwise}\f]

That is, MHI pixels where the motion occurs are set to the current timestamp , while the pixels where the motion happened last time a long time ago are cleared.

The function, together with calcMotionGradient and calcGlobalOrientation , implements a motion templates technique described in \cite Davis97 and \cite Bradski00 .

calcMotionGradient

@Namespace(value="cv::motempl")
public static void calcMotionGradient(@ByVal
                                     opencv_core.Mat mhi,
                                     @ByVal
                                     opencv_core.Mat mask,
                                     @ByVal
                                     opencv_core.Mat orientation,
                                     double delta1,
                                     double delta2,
                                     int apertureSize)

\brief Calculates a gradient orientation of a motion history image.

Parameters:

mhi - Motion history single-channel floating-point image.

mask - Output mask image that has the type CV_8UC1 and the same size as mhi . Its non-zero elements mark pixels where the motion gradient data is correct.

orientation - Output motion gradient orientation image that has the same type and the same size as mhi . Each pixel of the image is a motion orientation, from 0 to 360 degrees.

delta1 - Minimal (or maximal) allowed difference between mhi values within a pixel neighborhood.

delta2 - Maximal (or minimal) allowed difference between mhi values within a pixel neighborhood. That is, the function finds the minimum ( \f$m(x,y)\f$ ) and maximum ( \f$M(x,y)\f$ ) mhi values over \f$3 \times 3\f$ neighborhood of each pixel and marks the motion orientation at \f$(x, y)\f$ as valid only if \f[\min ( \texttt{delta1} , \texttt{delta2} ) \le M(x,y)-m(x,y) \le \max ( \texttt{delta1} , \texttt{delta2} ).\f]

apertureSize - Aperture size of the Sobel operator.

The function calculates a gradient orientation at each pixel \f$(x, y)\f$ as:

\f[\texttt{orientation} (x,y)= \arctan{\frac{d\texttt{mhi}/dy}{d\texttt{mhi}/dx}}\f]

In fact, fastAtan2 and phase are used so that the computed angle is measured in degrees and covers the full range 0..360. Also, the mask is filled to indicate pixels where the computed angle is valid.

\note - (Python) An example on how to perform a motion template technique can be found at opencv_source_code/samples/python2/motempl.py

calcMotionGradient

@Namespace(value="cv::motempl")
public static void calcMotionGradient(@ByVal
                                     opencv_core.Mat mhi,
                                     @ByVal
                                     opencv_core.Mat mask,
                                     @ByVal
                                     opencv_core.Mat orientation,
                                     double delta1,
                                     double delta2)

calcGlobalOrientation

@Namespace(value="cv::motempl")
public static double calcGlobalOrientation(@ByVal
                                          opencv_core.Mat orientation,
                                          @ByVal
                                          opencv_core.Mat mask,
                                          @ByVal
                                          opencv_core.Mat mhi,
                                          double timestamp,
                                          double duration)

\brief Calculates a global motion orientation in a selected region.

Parameters:

orientation - Motion gradient orientation image calculated by the function calcMotionGradient

mask - Mask image. It may be a conjunction of a valid gradient mask, also calculated by calcMotionGradient , and the mask of a region whose direction needs to be calculated.

mhi - Motion history image calculated by updateMotionHistory .

timestamp - Timestamp passed to updateMotionHistory .

duration - Maximum duration of a motion track in milliseconds, passed to updateMotionHistory

The function calculates an average motion direction in the selected region and returns the angle between 0 degrees and 360 degrees. The average direction is computed from the weighted orientation histogram, where a recent motion has a larger weight and the motion occurred in the past has a smaller weight, as recorded in mhi .

segmentMotion

@Namespace(value="cv::motempl")
public static void segmentMotion(@ByVal
                                opencv_core.Mat mhi,
                                @ByVal
                                opencv_core.Mat segmask,
                                @ByRef
                                opencv_core.RectVector boundingRects,
                                double timestamp,
                                double segThresh)

\brief Splits a motion history image into a few parts corresponding to separate independent motions (for example, left hand, right hand).

Parameters:

mhi - Motion history image.

segmask - Image where the found mask should be stored, single-channel, 32-bit floating-point.

boundingRects - Vector containing ROIs of motion connected components.

timestamp - Current time in milliseconds or other units.

segThresh - Segmentation threshold that is recommended to be equal to the interval between motion history "steps" or greater.

The function finds all of the motion segments and marks them in segmask with individual values (1,2,...). It also computes a vector with ROIs of motion connected components. After that the motion direction for every component can be calculated with calcGlobalOrientation using the extracted mask of the particular component.